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Tele-operative task environment interface with identification of greenhouse watermelon under natural light

Tele-operative task environment interface with identificatio...

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IEEE/ASME (AIM) International conference on advanced Intelligent Mechatronics

作者： Si-Chan Kim Heon Hwang Robotics & Vision Laboratory Department of Bio-Mechattonic Engineering Faculty of Life Science & Technology Sungkyunkwan University Suwon Gyeonggi South Korea

ISBN: (纸本)0780377591

Computer vision technology has been utilized as one of the most powerful tools to automate various agricultural operations. Though it has demonstrated successful results in various applications, the current status of technology is still far behind the human's capability typically for the unstructured and variable task environment. In this paper, a man-machine interactive hybrid decision-making system which utilized a concept of tele-operation was proposed to overcome limitations of computer image processing and cognitive capability. Tasks of greenhouse watermelon cultivation such as pruning, watering, pesticide application, and harvest require identification of target object. Identifying watermelons including position data from the field image is very difficult because of the ambiguity among stems, leaves, shades, and fruits, especially when watermelon is covered partly by leaves or stems. Watermelon identification from the cultivation field image transmitted by wireless was selected to realize the proposed concept. The system was designed such that operator (former), computer, and machinery share their roles utilizing their maximum merits to accomplish given tasks successfully. And the developed system was composed of the image monitoring and task control module, wireless remote image acquisition and data transmission module, and man-machine interface module. Once task was selected from the task control and monitoring module, the analog signal of the color image of the field was captured and transmitted to the host computer using R.F. module by wireless. Operator communicated with computer through touch screen interface. And then a sequence of algorithms to identify the location and size of the watermelon was performed based on the local image processing. And the system showed practical and feasible way of automation for the volatile bio-production process.

关键词： Application software Image processing Computerized monitoring Remote monitoring Computer vision Man machine systems Decision making Object recognition Machinery Control systems

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Washing Machine's Working States Recognition Based on Audio Fusion Feature

Washing Machine's Working States Recognition Based on Audio ...

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advanced algorithms and Control Engineering (ICAACE), International conference on

作者： Siqiang Xu Cuiyun Gao Yang Zhao Zengyuan Wu Fei Du Hongqiang Wang Power Quality Analysis and Load Detection Technology Laboratory Anhui Jianzhu University Hefei China Whirlpool (China) corporation Global R&D Center Hefei China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

In order to effectively determine the normal working status of smart home appliances, this paper realizes the recognition of washing machine's working states based on audio signals of microphone array (6 sensors). The paper proposes a fusion classification method combining optimizing STFT features and LSTM, and compares multi-channel feature fusion and voting classification methods. Determine the relatively optimal frequency resolution feature by changing the frequency resolution of STFT. The multi-channel feature fusion classification method is to concatenate the features of six different channels, input them into the LSTM network model for training, and obtain a comprehensive LSTM classifier. Voting fusion classification method: Train a LSTM network model independently for each channel's feature, and obtain 6 corresponding LSTM sub-classifiers, and then vote for the predicted classes of 6 channels corresponding to the same sample to obtain the fusion classification result. A vertical axis washing machine is taken to verify the proposed method, the experiment results show that both fusion classification methods have better performance than single channel methods. Compared with the multi-channel feature fusion method, the recognition rate of the multi-channel feature fusion method is slightly higher than that of the voting classification method, with a maximum of 99.7%.

关键词： Training Working environment noise Wheels signal processing algorithms Smart homes Microphone arrays Washing machines

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Network enabled cardiac monitor

Network enabled cardiac monitor

引用

IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Amna Arouj Shoab A. Khan Faiza Rahat Sadaf Ayaz Aymen Malik College of Electrical and Mechanical Engineering National University of Sciences and Technology

Heart diseases and stroke count up to 25% of all the deaths in the world, while 90% of them can be prevented if timely medical actions can be taken. With a very few and distant cardiac hospitals present in developing countries like Pakistan, people especially living in remote areas have no access to the cardiologists. This paper presents development of a portable system for real time analysis of ECG signals, capable of monitoring and detecting abnormalities occurring in the heart activity without the help of an expert. It can either be used as an intelligent holter device or an advanced warning device. It is very important for a range of clinical and diagnostic devices. The proposed portable system uses an online ECG library of patient data, which is filtered for noise firstly, and then the features present on the strip of ECG i.e., QRS complex, RR interval, ST segment and p wave are extracted. Early changes in the heart muscle activity after a heart disease reflects on these points, thus with the help of these features the system then classifies the ECG signal as normal or abnormal using real time algorithms for the early diagnosis of four various heart diseases. The results are then updated on the hospital's server wirelessly thus reducing the communication gap between a doctor and patient.

关键词： Electrocardiography Heart Wavelet transforms Diseases Turning Feature extraction signal processing algorithms

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Augmented Reality and Artificial Intelligence in Sign Language Expression

Augmented Reality and Artificial Intelligence in Sign Langua...

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IEEE International conference on Intelligent Techniques in Control, Optimization and signal processing (INCOS)

作者： Kaviyaraj R P. Sathya P. Nandhini Vinoth Kumar P Sureshkumar Chelliah Ezhilmathi S Department of computational intelligence SRM institute of science and technology Kattankulathur India Department of Computer Science and Engineering Sri Shanmuga Collage of Engineering and Technology Sankari India Department of Artificial Intelligence and Data Science St. Joseph's Institute of Technology OMR Chennai

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361193

Sign language, the vibrant tapestry of hand gestures and facial expressions, is the lifeblood of Deaf and hardof-hearing communities. For millions of signers, American Sign Language (ASL) runs deeper than communication, fundamental to identity, expression, and belonging. And yet an unshakeable communication gap leaves users of ASL frequently marooned away from the hearing world, kept from education, healthcare, or employment, or from basic, everyday transactions. By posing this new unsolved challenge to the power and promise of Artificial Intelligence (AI), this work leads the way towards closing that chasm by real-time recognition and translation of full ASL. Our approach employs a novel variant of Random Forest and utilizes cutting-edge video processing techniques to identify and understand the nuanced, often exquisitely delicate detail of ASL signing, at unprecedented levels of accuracy, and at speed. Another layer of innovation that characterizes our work is our integration of augmented reality (AR). By embedding AR along with our translator of artificial intelligence tech, we intend to completely change the way American Sign Language (ASL) is conveyed by directly engraining our already robust Random Forest model and advanced video processing techniques to project the ASL translation directly into your visual field in real time. The goal to demystify this complex and vivid language and, in doing so, to remove the communication barriers that persist between the Deaf community and the rest of the world, thus, fostering inclusion.

关键词： Sign language Computational modeling signal processing algorithms Assistive technologies Predictive models Streaming media Feature extraction

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Considerations to Spoken Language Recognition for Text-to-Speech Applications

Considerations to Spoken Language Recognition for Text-to-Sp...

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International conference on Computer Modeling and Simulation, UKSIM

作者： M. Saadeq Rafieee Somayeh Jafari Hesamoddin Shahriari Ahmadi Masumeh Jafari IEEE Signal Processing Society Member Islamic Azad University Iran Islamic Azad University Mashhad Branch somaye Department of English hesam Ferdowsi University of Mashhad Iran Shahid Bahonar University슠of슠Kerman Iran Shahid Banohar University of Kerman

There have been a great deal of discussions throughout the past few years over whether or not Text-to-Speech (TTS) machines can synthesize natural synthetic speech from texts. Aiming to address this need, in this paper we have considered some significant viewpoints of Spoken Language processing (SLP) on the phonetic transcription of each word for the preprocessing of text-to-speech synthesis. On the other hand, lack of researches on automatic language detection for text transcription in different languages by considering the phonology of that language, motivated us to make a text language identifier system for commonly-used contexts. It therefore encouraged us to conduct a novel research into semi-English texts that people from different nations often use in their conversational transcripts such as email or chat via the Internet or cell phone text messaging services. In this research, we have investigated the language of text sequences by employing phonotactics rules, chiefly on Finglish (a portmanteau term combining Farsi and English) which is an alternative writing format for the Farsi Language, which has its own orthographic system, by means of English letters. As this is the first paper regarding Finglish texts, it can be tremendously exciting to enhance the text-to-speech synthesis systems created by advanced Digital signal processing (DSP) algorithms to specifying the language of each sentence in the first place. Finally, we have also proposed highly recommended writing rules for Finglish for it to be easily understood, translated to English and converted to natural speech.

关键词： Speech Spectrogram Google Speech recognition Speech processing Stress Dictionaries

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Tri-axial telecoil hearing aid for improved connection to public induction loops

Tri-axial telecoil hearing aid for improved connection to pu...

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Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Timothy H. Riehle Robert J. Knuesel Patrick A. Lichter Dorin Panescu Koronis Biomedical Technologies Inc Maple Grove MN USA Advanced Cardiac Therapeutics Santa Clara CA

Telecoils in hearing aids serve a dual purpose: to enhance telephone conversation and enable hearing aids to serve as a wireless interface for public audio broadcasts. When broadcasting audio signals, the signal is transmitted to the telecoil sensor (a magnetic field sensor located in the hearing aid) via magnetic energy from an induction wire loop located near the listener. This induction loop can be a small assembly located in the handset of the telephone or a large wire loop within a public venue like a theatre. Current hearing aids detect the magnetic signal using a single telecoil. If the telecoil is not aligned with the magnetic field, the strength of the detected signal is diminished. Unfortunately, public induction loops and telephone handsets seldom share a common alignment to the hearing aid, leading to sub-optimal performance by one or both in hearing aids available today. In this research, a prototype behind-the-ear (BTE) hearing aid with tri-axial telecoils was developed and DSP algorithms to process and combine the three signals were developed. The resulting hearing aid was evaluated in a human trial and provided better performance than a similar quality conventional telecoil hearing aid.

关键词： Auditory system Digital signal processing Hearing aids Channel estimation Prototypes signal to noise ratio Speech

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Electrode selection and other design considerations for a modular, portable single-channel EEG-augmented hearing aid

Electrode selection and other design considerations for a mo...

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International IEEE/EMBS conference on Neural Engineering, CNE

作者： Noah B. Brummer Joseph A. Rawson Matthew W. Grimm Patrick Tupper Ashley J. L. Miller Curtis J. Billings Peter G. Jacobs Portland State University Research Investigators National Center for Rehabilitative Auditory Research Portland Biomedical Engineering Department Oregon Health & Science University

In this paper, we present a design for a portable single-channel EEG-controlled hearing aid. The design has relevance for future versions of hearing aids that may make use of electroencephalography (EEG) to control the settings and signal processing on the hearing aid. The design also has relevance for auditory-based brain-computer interface (BCI) systems. Current hearing aid technology uses only acoustic information to perform noise removal algorithms and to do directional beamforming using array microphones. Recent advances in EEG and applications in auditory-based BCI have opened the door for the potential use of EEG information to automatically control the function of a hearing aid. In this paper we describe the design of a modular mobile hearing aid platform that accepts EEG inputs. We have investigated which electrodes are the most relevant for performing an EEG-based classifier of oddball sounds using tones and nonsense syllables so that eventually a minimal set of electrodes may be used in a portable auditory-based EEG BCI system. And we have described the modular design of a portable hearing aid system which enables interchange of different USB-enabled EEG electrodes, codecs, and battery supplies. The system includes a dual-microphone array for enabling adaptive beamforming noise cancelation and a Linux-based processor for performing advanced noise cancelation and compression algorithms.

关键词： Electroencephalography Auditory system Electrodes Microphones Array signal processing Accuracy Codecs

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The Research of Amplitude Threshold Method in Ultrasound-based Indoor Distance-Measurement System 20

The Research of Amplitude Threshold Method in Ultrasound-bas...

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Proceedings of the 2020 4th International conference on Electronic Information Technology and Computer Engineering

作者： Lu Lu Weiquan Ye Jinxu Tao School of Food and Advanced Technology Massey University Auckland New Zealand School of Information Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9781450387811

In this paper, an amplitude threshold algorithm (ATA) is proposed to estimate time of flight (ToF) of ultrasound signal (US) under high signal noise ratio (SNR) in ultrasound-based indoor distance-measurement system. The purpose of the research is to accurately measure ToF of US and further calculate the distance between ultrasound transceiver. ATA determines ToF based on the time when the monitored signal amplitude first goes above a corresponding threshold. ATA can achieve accurate ToF estimation under high SNR. Furthermore, compared to other ToF estimation algorithms, ATA has the lower algorithm complexity leading to shorter processing time, therefore, ATA is appropriate for the real-time dynamic measurement. In this research, an ultrasound-based indoor distance-measurement system was generated to synchronize the input and output of analog signal and provide high-quality signal. ATA estimated the distance between ultrasound transceiver in the range of 5 meters. The experimental result shows that ATA has relatively high accuracy under high SNR and fast processing speed. Based on the distance-measurement system, an ultrasound-based indoor localization system which aims to localize a static object on two dimensions could be established in the future, some preparatory works has been done and the architecture of the localization system is presented.

关键词： Ultrasound signal (US) Time of flight (ToF) Amplitude threshold algorithm (ATA) signal noise ratio (SNR)

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An AMCMD Approach for Robust EEG signal Classification: Unraveling Neurophysiological Insights and BCI Applications

An AMCMD Approach for Robust EEG Signal Classification: Unra...

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International conference on Information, Communication and Networks (ICICN)

作者： Muhammad Zulkifal Aziz Xiaojun Yu School of Automation Northwestern Polytechnical University Xi’an China

Electroencephalogram (EEG) signal processing plays a pivotal role in deciphering profound neurophysiological insights from seemingly inconspicuous neural signals, enabling the realization of practical BCI applications. This paper delves into an innovative and sophisticated EEG signal processing model, which employs three distinct combinations of EEG electrodes, four advanced feature extraction methods, and four cutting-edge classification algorithms, in conjunction with an adaptive multivariate chirp mode decomposition (AMCMD) for the analysis of motor imagery EEG signals. The feasibility of this novel approach is corroborated through its successful application to a sizable GigaDB dataset comprising 52 participants, as well as the challenging BCI competition III datasets IVa and IVb. The results unequivocally demonstrate that the seamless integration of the AMCMD mechanism with an 18-electrode combination, spectral features, and a multilayer neural network classifier engenders remarkably robust and discriminating classification outcomes. The classification accuracy for dataset IVa and IVb subjects attains an impressive pinnacle, reaching 99.70%, 99.88%, 99.88%, 99.87%, 100%, and 94.98%, respectively. Furthermore, when scrutinizing the GigaDB dataset, the average classification accuracy, sensitivity, specificity, and f1score exhibit commendable values of 82.71%, 82.76%, 83.04%, and 82.80%, respectively. These salient findings, juxtaposed against the backdrop of earlier studies, decisively manifest a striking 15.4% enhancement in average classification accuracy, irrefutably affirming the exceptional prowess of the proposed model. Consequently, the compelling evidence culminates in the conclusion that the adaptive AMCMD method stands resolutely robust, adept, and universally adaptive in its ability to proficiently classify EEG signals, deftly circumventing subject-to-subject variability across diverse and extensive datasets.

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Implementation of Speech processing Techniques for Human Emotion Recognition

Implementation of Speech Processing Techniques for Human Emo...

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Computational Intelligence for Green and Sustainable Technologies (ICCIGST), International conference on

作者： Bvv Padmavathi D. Ganesh M. Sunil Kumar Mungara Kiran Kumar Vamsidhar Talasila B. Neelambaram velagapudi ramakrishna siddhartha engineering college Kanuru Vijayawada Andhra Pradesh India Erstwhile Sree Vidyanikethan Engineering College(Autonomous) mohan babu university Tirupati Andhra Pradesh India Department of CSE School of Technology GITAM(Deemed to be university) Hyderabad Department of Computer Science and Engineering koneru lakshmaiah education foundation Green fields Vaddeswaram Guntur Andhra Pradesh India

ISBN: (数字)9798350381887

ISBN: (纸本)9798350381894

Emotion identification from speech signals has been a research issue in human machine interaction applications for many years. Emotions incredibly play a vital role in our mental functioning. SER is the process of identifying an individual speaker’s emotional state through the speech stream. The purpose of emotion recognition using speech processing is to develop a system that cans precisely asses a person’s emotional state based on their speech signals. They would use machine learning algorithms to analyze features such as pitch, tone, rhythm, and intensity of speech, and then classify the emotions expressed in the speech as happy, sad, angry, fearful, or neutral. The main applications of emotion recognition using speech processing include human-computer interaction, psychotherapy, and customer service. Inhuman-computer interaction, emotion recognition systems can provide more personalized and empathetic responses, enhancing the user experience. By analyzing their patients’ facial expressions and body language, therapists using emotion recognition systems in psychotherapy can better meet the needs of their patients. In customer service, emotion recognition systems can help companies to improve their customer satisfaction by detecting and responding to negative emotions expressed by customers. Neutral, Anger, Being happy, & Sadness are some of the few universal emotions that can be taught to any intelligent system with limited processing resources and ability to recognize and synthesize. as required. Mel-frequency cepstral coefficients (MFCC), a chromogram, a Mel scale spectrogram are extracted together with Tonal Centroid and Spectral Contrast characteristics. Deep Neural Network is used to understand human emotions, advanced signal processing techniques, and sophisticated machine learning algorithms.

关键词： Human computer interaction Emotion recognition Machine learning algorithms Customer services Speech recognition User experience Recording Speech processing Mel frequency cepstral coefficient Spectrogram

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